It is possible that much can be learned from examining the effect of workforce factors in nursing homes, given the almost intransigent low quality seen in many of these facilities. Although past research in this area as examined the effect of turnover and staffing levels on quality, there have been very few studies that have examined the impact of multiple workforce factors or that have looked at whether different characteristics of the workforce interact to produce either good or bad quality. Thus, prior underspecified models may have served to limit somewhat our understanding of which workforce factors influence most (least) quality of care. In addition, only weak evidence exists that staff ratios influence quality of care, again probably due to the underspecified nature of most investigations. [unreadable] [unreadable] In this research, we propose to examine the influence that multiple staffing characteristics, specifically [unreadable] turnover, staffing levels, worker stability, and agency staff, has on quality of care in a large sample of nursing homes. We believe that nursing home residents have increasingly more complex care needs, and facilities are using increasingly complex technology. Care is also dependent not only on how much is done, but upon what is done, how well it is done, when it is done, and by whom. Thus, simply adding more staff may be a necessary but not sufficient means of improving quality. Examining care processes more adequately is important, and may lead to broader policy debate over staffing issues rather than staffing levels in nursing homes. [unreadable] [unreadable] In preliminary analyses, we have identified staffing levels, turnover, stability, and use of agency staff as significant influences on quality. In this project, we propose to extend this prior research, by using a larger sample, more refined measures of quality, and better specified staffing characteristic variables. We will merge data collected from a unique survey on turnover from 2,946 nursing homes with data from: the Minimum Data Set (MDS), the On-line Survey Certification and Recording (OSCAR) system, and the Area Research File (ARF). Staffing characteristics will come from the primary data, resident characteristics and quality indicators will come from the MDS, facility characteristics will come from the OSCAR, and market characteristics will come from the ARF. We will examine the associations between staffing levels, turnover, stability, and use of agency staff and quality, not only for licensed practical nurses (LPNs), and registered nurses (RNs), but also for nurse aides (NAs). [unreadable] [unreadable] [unreadable]